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  • 标题:A Quantitative Model of Yorùbá Speech Intonation Using Stem-ML.
  • 本地全文:下载
  • 作者:Odetunji A. Odejobi.
  • 期刊名称:INFOCOMP
  • 印刷版ISSN:1807-4545
  • 出版年度:2007
  • 卷号:6
  • 期号:3
  • 页码:47-55
  • 出版社:Federal University of Lavras
  • 摘要:We present a quantitative model of Standard Yor¨´b¨¢ (SY) intonation; it is designed to have parameters that are linguistically interpretable. The model is built and trained on speech data from a native speaker of SY. The resulting model reproduces the data well: its Root Mean Square prediction error (RMSE) is 14:00 Hz on a test set. We find that intonation is used to mark sentence and phrase boundaries: beginning syllables are systematically stronger, while ending syllables are systematically weaker than the medial syllables. The M tone is the strongest and the H tone is the weakest, though the differences are modest. We see comparable amounts of carry-over and anticipatory co-articulation. The resulting model for SY shows similar characteristics when compared to Mandarin and Cantonese intonation models.
  • 关键词:Intonation modelling, Speech synthesis, Quantitative model
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